Janna E. Johnson
University of Minnesota

Stephan D. Whitaker
Federal Reserve Bank of Cleveland

Abstract

This paper demonstrates that credit bureau data, such as the Federal Reserve Bank of New York Consumer Credit Panel/Equifax (CCP), can be used to study internal migration in the United States. It is comparable to, and in some ways superior to, the standard data used to study migration, including the American Community Survey (ACS), the Current Population Survey (CPS), and the Internal Revenue Service (IRS) county-to-county migration data. CCP-based estimates of migration intensity, connectivity, and spatial focusing are similar to estimates derived from the ACS, CPS, and IRS data. The CCP can measure block-to-block migration and it is available at quarterly rather than annual frequencies. Migrants’ precise origins are not available in public versions of the ACS, CPS, or IRS data. We report measures of migration from the CCP data at finer geographies and time intervals. Finally, we disaggregate migration flows into first-, second-, and higher-order moves. Individual-level panels in the CCP make this possible, giving the CCP an additional advantage over the ACS, CPS, or publicly available IRS data.